DBMS > BigObject vs. Firebase Realtime Database vs. Riak TS vs. Weaviate

System Properties Comparison BigObject vs. Firebase Realtime Database vs. Riak TS vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Time Series DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

bigobject.io

firebase.google.com/products/realtime-database

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.bigobject.io

firebase.google.com/docs/database

www.tiot.jp/riak-docs/riak/ts/latest

weaviate.io/developers/weaviate

Developer

BigObject, Inc.

Google

acquired by Google 2014

Open Source, formerly Basho Technologies

Weaviate B.V.

Initial release

2015

2012

2015

2019

Current release

3.0.0, September 2022

1.19, May 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
OS X

Data scheme

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

restricted

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes, limited

GraphQL is used as query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Native Erlang Interface

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

Erlang

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes, based on authentication and database rules

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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